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Local Indicators of Spatial Association—LISA
Open accessAbstract
The capabilities for visualization, rapid data retrieval, and manipulation in geographic information systems (GIS) have created the need for new techniques of exploratory data analysis that focus on the “spatial” aspects of the data. The identification of local patterns of spatial association is an important concern in this respect. In this paper, I outline a new general class of local indicators of spatial association (LISA) and show how they allow for the decomposition of global indicators, such as Moran's I, into the contribution of each observation. The LISA statistics serve two purposes. On one hand, they may be interpreted as indicators of local pockets of nonstationarity, or hot spots, similar to the G i and G*i statistics of Getis and Ord (1992). On the other hand, they may be used to assess the influence of individual locations on the magnitude of the global statistic and to identify “outliers,” as in Anselin's Moran scatterplot (1993a). An initial evaluation of the properties of a LISA statistic is carried out for the local Moran, which is applied in a study of the spatial pattern of conflict for African countries and in a number of Monte Carlo simulations.
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Cites
Regression Diagnostics: Identifying Influential Data and Sources of Collinearity
Belsley, D. A., Kuh, E., & Welsch, R. E. (1980) · Wiley Series in Probability and Statistics · doi:10.1002/0471725153 · Cited by 7,297
Cited by
Spatial Analysis: A Guide for Ecologists
Fortin, M.-J., & Dale, M. R. T. (2005) · doi:10.1017/cbo9780511542039 · Cited by 991
Harlan, S. L., Declet-Barreto, J. H., Stefanov, W. L., & Petitti, D. B. (2013) · Environmental Health Perspectives · doi:10.1289/ehp.1104625 · Cited by 507
RATCLIFFE, J. H., TANIGUCHI, T., GROFF, E. R., & WOOD, J. D. (2011) · Criminology · doi:10.1111/j.1745-9125.2011.00240.x · Cited by 436
Miller, H. J., & Goodchild, M. F. (2015) · GeoJournal · doi:10.1007/s10708-014-9602-6 · Cited by 391
Shannon, S. K. S., Uggen, C., Schnittker, J., Thompson, M., Wakefield, S., & Massoglia, M. (2017) · Demography · doi:10.1007/s13524-017-0611-1 · Cited by 356
Metadata
- Authors
- Anselin, L.
- Venue
- Geographical Analysis
- Publisher
- Wiley
- Published
- 1995-04
- Volume
- 27
- Issue
- 2
- Pages
- 93-115
- ISSN
- 0016-7363 (ISSN-L)
- 1538-4632
- OpenAlex
- W2118898434
- Cited by
- 12,919
- References
- 1
- FWCI
- 59.56
- Type
- journal article
- Language
- en
- Open access
- bronze
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